create-specification

Generate structured specification documents in Markdown for AI consumption.

Updated Mar 9, 2026
One-click install
npx skills add https://github.com/Cripacx/agentic-dotnet --skill create-specification-cripacx
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: create-specification
Source: https://github.com/Cripacx/agentic-dotnet/tree/main/skills/create-specification
Command: npx skills add https://github.com/Cripacx/agentic-dotnet --skill create-specification-cripacx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the creation of detailed, structured specification files optimized for consumption by Generative AI models, ensuring clarity and consistency in project documentation.

Core Features & Use Cases

  • AI-Optimized Format: Generates specifications adhering to best practices for machine readability and unambiguous interpretation.
  • Structured Content: Includes sections for purpose, scope, definitions, requirements, interfaces, acceptance criteria, and more.
  • Use Case: When starting a new feature development, use this skill to generate a comprehensive specification document that clearly outlines all requirements and constraints for the AI to follow during implementation.

Quick Start

Use the create-specification skill to generate a specification for a new user authentication module.

Frequently Asked Questions about create-specification

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate AI-ready specification documents for feature development?

To generate AI-ready specifications, you define the purpose, scope, and acceptance criteria to produce a structured Markdown file optimized for generative AI consumption. This ensures unambiguous interpretation by models during implementation.

What is an AI-optimized specification and when do I need one?

An AI-optimized specification is a structured document defining requirements, constraints, and interfaces in a machine-readable format. You need it when starting feature development to ensure AI models clearly understand and follow implementation guidelines.

How do I structure requirements and constraints for generative AI consumption?

You structure requirements by using a predefined Markdown template that separates purpose, definitions, interfaces, and acceptance criteria. This creates an unambiguous, machine-readable format that guides generative AI output accurately.

Does this specification template work for defining user authentication modules?

Yes, the specification template works for defining user authentication modules by capturing all requirements, interfaces, and acceptance criteria in a structured Markdown format. It clearly outlines constraints for the AI to follow during implementation.

What's the best way to create machine-readable documentation for AI models?

The best way to create machine-readable documentation is to use a structured Markdown template that explicitly defines scope and acceptance criteria. This ensures the generated specification is clear, unambiguous, and optimized for AI consumption.

Where are generated specification files saved and how are they named?

Generated specification files are saved in the /spec/ directory using a descriptive naming convention. This organizes structured Markdown documents systematically for easy retrieval during AI-driven implementation.